ArticleVaccine2020
Ensemble forecast modeling for the design of COVID-19 vaccine efficacy trials.
Article in Vaccine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
18 citing papers in PubMed.
- Multi-Model Ensembles in Infectious Disease and Public Health: Methods, Interpretation, and Implementation in R.Statistics in medicine · 2026Article
- Mathematical modelling for vaccine efficacy trials during the future epidemics of emerging respiratory infections.Human vaccines & immunotherapeutics · 2025Article
- Machine learning for predicting severe dengue in Puerto Rico.Infectious diseases of poverty · 2025Article
- An Epidemic Model with Infection Age and Vaccination Age Structure.Infectious disease reports · 2024Article
- An implementation framework to improve the transparency and reproducibility of computational models of infectious diseases.PLoS computational biology · 2023Article
- A spatiotemporal machine learning approach to forecasting COVID-19 incidence at the county level in the USA.International journal of data science and analytics · 2023Article
- Mathematical Models for Cholera Dynamics-A Review.Microorganisms · 2022Review
- An epidemic-economic model for COVID-19.Mathematical biosciences and engineering : MBE · 2022Article
- Aggregating human judgment probabilistic predictions of the safety, efficacy, and timing of a COVID-19 vaccine.Vaccine · 2022Article
- A random forest model for forecasting regional COVID-19 cases utilizing reproduction number estimates and demographic data.Chaos, solitons, and fractals · 2022Article
- Interval forecasts of weekly incident and cumulative COVID-19 mortality in the United States: A comparison of combining methods.PloS one · 2022Article
- Article
- Burden is in the eye of the beholder: Sensitivity of yellow fever disease burden estimates to modeling assumptions.Science advances · 2021Article
- Using simulated infectious disease outbreaks to inform site selection and sample size for individually randomized vaccine trials during an ongoing epidemic.Clinical trials (London, England) · 2021Article
- A pre-registered short-term forecasting study of COVID-19 in Germany and Poland during the second wave.Nature communications · 2021Article
- A COVID-19 Epidemic Model Predicting the Effectiveness of Vaccination in the US.Infectious disease reports · 2021Article
- COVID-19 Vaccine Priority Strategy Using a Heterogenous Transmission Model Based on Maximum Likelihood Estimation in the Republic of Korea.International journal of environmental research and public health · 2021Article
- Comparing trained and untrained probabilistic ensemble forecasts of COVID-19 cases and deaths in the United States.International journal of forecastingArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors.
Funding
Abstract
To rapidly evaluate the safety and efficacy of COVID-19 vaccine candidates, prioritizing vaccine trial sites in areas with high expected disease incidence can speed endpoint accrual and shorten trial duration. Mathematical and statistical forecast models can inform the process of site selection, integrating available data sources and facilitating comparisons across locations. We recommend the use of ensemble forecast modeling - combining projections from independent modeling groups - to guide investigators identifying suitable sites for COVID-19 vaccine efficacy trials. We describe an appropriate structure for this process, including minimum requirements, suggested output, and a user-friendly tool for displaying results. Importantly, we advise that this process be repeated regularly throughout the trial, to inform decisions about enrolling new participants at existing sites with waning incidence versus adding entirely new sites. These types of data-driven models can support the implementation of flexible efficacy trials tailored to the outbreak setting.
Indexed as
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.